A method and system receives a digital source image and brush size data. The source image is blurred to generate a digital reference image. The brush size data includes a first record corresponding to a first size of a brush and a second record corresponding to a second size of the brush. The first size is different from the second size. The method and system applies brush strokes, with the first record to be used for the brush, to a digital canvas image using the reference image. Then the brush strokes are applied, with the second record to be used for the brush, to the canvas image using the reference and working images. Thus, a final digital image having a hand-painted appearance is generated on the canvas image. Long curved brush strokes can also be used to generate the target image, which is aligned in a normal direction to image gradients. Furthermore the graphic artist may adjust parameters of the method and system according to the present invention to vary the style of painting.

Patent
   6011536
Priority
Apr 17 1998
Filed
May 22 1998
Issued
Jan 04 2000
Expiry
May 22 2018
Assg.orig
Entity
Small
155
11
all paid
1. A method for generating a digital finalized image having a hand-painted appearance on a digital canvas image using a computer system, the method comprising the steps of:
(a) receiving a digital source image;
(b) blurring the source image to generate a digital reference image;
(c) receiving brush size data, the brush size data including a first record corresponding to a first size of a brush and a second record corresponding to a second size of the brush, the first size being different from the second size;
(d) with the first record for the brush, applying brush strokes to the canvas image using the reference image; and
(e) with the second record for the brush and after step (d), applying the brush strokes to the canvas image using the reference and canvas images.
15. A system for generating a digital image having a hand-painted appearance on a canvas image, comprising:
a device providing a source image and brush size data; and
a processor blurring the source image to generate a reference image and receiving the brush size data, the brush size data including a first record corresponding to a first size of a brush and a second record corresponding to a second size of the brush, the first size being different from the second size,
wherein the processor, with the first record for the brush, applies brush strokes to the canvas image using the reference image to generate a working image, and
wherein the processor, with the second record for the brush, applies the brush strokes to the working image using the reference and working images to generate a finalized image.
2. The method according to claim 1, further comprising the step of:
(f) displaying the canvas image on a display device.
3. The method according to claim 1, further comprising the step of:
(f) storing the canvas image using in a storage device.
4. The method according to claim 1, wherein the first size of the brush is greater than the second size of the brush.
5. The method according to claim 4, wherein the brush size data includes a third record corresponding to a third size of the brush, the third size being smaller than the second size, and further comprising the step of:
(g) with the third record for the brush and after step (e), applying the brush strokes to the canvas image using the reference and canvas images.
6. The method according to claim 1, wherein step (d) includes the substeps of:
(i) overlaying a grid over the canvas image to generate grid locations, and
(ii) applying the brush strokes in a current location of the grid locations.
7. The method according to claim 6, wherein the brush strokes are applied in a direction being normal to a gradient of the current location.
8. The method according to claim 1, wherein step (e) includes the substeps of:
(i) overlaying a grid over the canvas image to generate grid locations,
(ii) comparing the canvas image and the reference image to generate difference values for each of the grid locations,
(iii) averaging the difference values of the difference locations around a current location to generate an averaged value,
(iv) determining a further location having a highest difference value, and
(v) applying the brush strokes in the further location if the averaged value is greater than a threshold value.
9. The method according to claim 8, wherein the brush strokes are applied in a direction being normal to a gradient of the further location.
10. The method according to claim 8, wherein the substep (v) includes the substeps of:
(v1) determining a first difference between a color of the reference image at the further location and a current color of the canvas image at the further location,
(v2) determining a second difference between a first color of the corresponding location and a second color of the brush stroke, and
(v3) continuing a curved brush stroke having a stroke length to another location on the canvas image if one of:
the stroke length is smaller than a maximum stroke length, and
the stroke length is larger than a minimum stroke length and the first difference is greater than the second difference.
11. The method according to claim 10, wherein the substep (v) further includes the substep of:
(v4) filtering a curvature of the curved brush stroke.
12. The method according to claim 1, further comprising the step of:
(g) receiving style data, wherein the brush strokes are applied to the canvas image using the style data.
13. The method according to claim 1, wherein step (d) includes the substep of:
storing each of the brush strokes in a list.
14. The method according to claim 1, wherein step (e) includes the substep of:
storing each of the brush strokes in a list.
16. The system according to claim 15, further comprising:
a display device displaying the finalized image.
17. The system according to claim 15, further comprising:
a storage device storing the finalized image.
18. The system according to claim 15, wherein the first size of the brush is greater than the second size of the brush.
19. The system according to claim 18, wherein the brush size data includes a third record corresponding to a third size of the brush, the third size being smaller than the second size, and wherein the processor, with the third record for the brush, applies the brush strokes to the finalized image using the reference and finalized images to generate a final image.
20. The system according to claim 15, wherein the processor applies the brush strokes to the canvas image by overlaying a grid over the canvas image to generate grid locations, and by applying the brush strokes in a current location of the grid locations.
21. The system according to claim 20, wherein the brush strokes are applied in a direction being normal to a gradient of the current location.
22. The system according to claim 15, wherein the processor applies the brush strokes over the working image by:
(a) overlaying a grid over the finalized image to generate grid locations,
(b) comparing the finalized image and the reference image to generate difference values for each of the grid locations,
(c) averaging the difference values of the difference locations around a current location to generate an averaged value,
(d) determining a further location having a highest difference value,
(e) generating control points in the further location if the averaged value is greater than a threshold value;
(f) connecting the control points to form the brush strokes.
23. The system according to claim 22, wherein the brush strokes are applied in a direction being normal to a gradient of the further location.
24. The system according to claim 22, wherein the processor applies the brush stroke in the further location by:
(a) determining a first difference between the further location and a corresponding location on the reference image,
(b) determining a second difference between a first color of the corresponding location and a second color of the brush strokes, and
(c) continuing a curved brush stroke having a stroke length to the further location on the finalized image if one of:
the stroke length is smaller than a maximum stroke length, and
the stroke length is larger than a minimum stroke length and the first difference is greater than the second difference.
25. The system according to claim 24, wherein the processor applies the brush stroke in the further location by:
(d) filtering a curvature of the curved brush stroke.
26. The system according to claim 24, wherein the brush strokes are applied to the canvas image using the style data.
27. The system according to claim 15, wherein the processor applies the brush strokes over the canvas image by:
storing each of the brush strokes in a list.
28. The system according to claim 15, wherein the processor applies the brush strokes over the working image by:
storing each of the brush strokes in a list.

This application claims benefit of provisional application 60/082245 filed Apr. 17, 1998.

The present invention relates to a method and system for generating an image having a hand-painted appearance. In particular, the generated image is created by repeatedly applying a series of spline brush strokes on a source image.

In the past, artistic illustrations have been solely created by skilled artists and creative individuals willing to devote considerable time and resources to the creation of such artistic illustrations. Current developments in a computer technology now enables a relatively quick and easy creation of photo realistic images. Accordingly, it is possible to automate details of photo realistic rendering. Such rendering processes are generally controlled by a human user selecting scenes and rendering parameters.

However, conventional processes and systems do not produce very good non-photo realistic works (i.e., paintings and drawings) having a hand-painted appearance in a fully automated manner. In particular, the human user utilizing these conventional processes and systems must interactively "paint" the entire image using a paint program or process an image or 3D model through a narrowly-defined set of non-photo realistic filters.

Some conventional methods and systems for processing an image do not produce images having non-photo realistic aspects. For example, these conventional processes and systems use very simple brush strokes, all of which have equal sizes and shapes. In contrast to hand-drawn paintings, the resulting images produced by these conventional processes and systems have mechanical and computer-generated appearance.

Thus, there is a need to overcome these disadvantages and provide a method and a system which produce non-photo realistic images without having the disadvantageous mechanical aspects.

A method and system according to the present invention provides a computer system to generate a digital image having a hand-painted appearance on a canvas image. This method and system receive a source image and brush size data. The source image is blurred to generate a reference image. The brush size data include a first record corresponding to a first size of a brush and a second record corresponding to a second size of the brush, the first size being different from the second size. The computer system operates to simulate brush strokes which are applied, with the first record to be used for the brush, to the canvas image using the reference image. The brush strokes are then applied, with the second record to be used for the brush, to the canvas image using the reference and canvas images. In this manner, an image having a hand-painted appearance is generated.

Thus, the target image is generated using a series of layers, starting with a rough sketch drawn, e.g., with a brush having a large size. The sketch is painted over with progressively smaller brushes, preferably in areas where the sketch differs from the blurred source image. Therefore, the visual emphasis in the painting corresponds approximately to the spatial energy present in the source image.

In another exemplary embodiment of the present invention, long curved brush strokes can be used to generate the target image, which is aligned in a normal direction to image gradients.

Furthermore the graphic artist may adjust parameters of the method and system according to the present invention to vary the style of painting.

FIG. 1 shows an overall system architecture of an exemplary embodiment of the system according to the present invention

FIG. 2 shows an exemplary rendering system of FIG. 1 according to the present invention in further detail.

FIG. 3 shows a general flow diagram of an exemplary embodiment of the method according to the present invention performed by the system according to the present invention.

FIG. 4(a) shows a digital source image to be used as a reference image.

FIG. 4(b) shows a digital canvas image after brush strokes having a largest supplied radius is applied on the canvas image.

FIG. 4(c) shows the digital canvas image of FIG. 4(b) after brush strokes having a smaller supplied radius are applied on the canvas image.

FIG. 4(d) shows the digital canvas image of FIG. 4(c) after the brush stroke having yet smaller supplied radius are applied on the canvas image.

FIG. 4(e) shows an exemplary illustration of a painting.

FIG. 4(f) shows a digital image generated using an exemplary procedure which may place a circle of the brush radius using a color of the digital source image.

FIG. 4(g) shows another digital image generated using short brush strokes aligned to a normal direction of image gradients.

FIG. 5 shows an exemplary embodiment of the method according to the present invention for painting a digital canvas image with a computer generated brush.

FIG. 6 shows a flowchart of an exemplary embodiment according to the present invention for generating a digital image using long curved brush strokes.

FIG. 7(a) shows an initial exemplary step in a procedure for applying long curved brush strokes on a canvas image.

FIG. 7(b) shows a second exemplary step in the procedure for applying long curved brush strokes on a canvas image.

FIG. 7(c) shows a third exemplary step in the procedure for applying long curved brush strokes on a canvas image.

FIG. 8(a) shows a first exemplary image illustrating "Impressionist", "Expressionist" and "Colorist Wash" styles in a top to bottom order.

FIG. 8(b) shows a second exemplary image illustrating "Impressionist", "Expressionist" and "Colorist Wash" styles in a top to bottom order.

FIG. 9(a) shows a "Pointillist" style digital image.

FIG. 9(b) shows a digital image generated when style parameters of the images in FIG. 9(a) and in FIG. 9(c) (described below) are averaged.

FIG. 9(c) shows a "Colorist Wash" style digital image.

Overall System Architecture

FIG. 1 shows an overall system architecture of an exemplary embodiment of the system according to the present invention. A user input device 20, an output device 30 and a source image arrangement 40 are coupled to a rendering system 10. The user input device 20 may include, e.g., a keyboard, a mouse and a voice command system, and is connected to the rendering system 10 via a first communication arrangement 15. The output device 30 may include, e.g., a monitor or a printer, and is connected to the rendering system 10 via a second communication arrangement 25. The source image arrangement 40 may include, e.g., a scanner, a storage arrangement maintaining stored images (such as a CD-ROM drive) and/or an Internet server storing source images. The source image arrangement 40 is connected to the rendering system 10 via a third communication arrangement 35. Each of the communication arrangements 15, 25, 35 may include, for example, a serial communication line, a parallel communication line, a fiber-optic communications network, etc. In addition, it is possible for the source image arrangement 40 to be incorporated into the rendering system 10.

The rendering system 10 may be connected to other rendering systems and/or to further systems (not shown) via a communication network and/or to telephone lines (not shown).

Message Delivery System

FIG. 2 shows the exemplary rendering system 10 according to the present invention in further detail. In particular, the exemplary rendering system 10 may include, for example, a processor 50. The processor 50 is coupled to a communications device 70 (e.g., a communications port such as SCSI port, a serial port, etc.), to an output port 60 (e.g., a monitor port, an LPT port, etc.) and to a storage device 80 (e.g., a RAM arrangement, a ROM arrangement, a disk drive, etc.). The processor 50 may include, for example, a high performance microprocessor, a minicomputer, a mainframe computer, or even a network of processors (which are commercially available). It should be noted that the output port 60, the communications device 70 and the storage device 80 are all commercially available.

The communications device 70 is preferably coupled to the source image arrangement 40 for receiving source images therefrom. In addition, the communications device 70 can be coupled to the user input device 20 for receiving user instructions therefrom. The communications device 70 can also be coupled to a communications network for communicating between other processors and/or systems. Such communications network may include analog telephone lines, digital telephone lines, an Ethernet network, T1/T3 communication arrangements, etc.

The source image may also be stored in the storage device 80, and therefore would be provided to the processor 50 during the execution of the method according to the present invention. As such, the rendering system 10 would be able to obtain the source image from the storage device 80 without utilizing the source image arrangement 40.

For displaying a processed image, the output device 30 is coupled to the output port 60 so that the image data may be provided from the output port 60 by the processor 50 and/or by the storage device 80.

In accordance with the present invention, the processor 50 controls the communications device 70, the storage device 80 and the output port 60 to receive, store and/or display the source images and to display the processed (e.g., final) image.

Overview Of Operation

FIG. 3 shows a general flow diagram of a method according to the present invention performed by the rendering system 10 described above. In particular, the method according to the present invention is initiated in step 100. The rendering system 10 receives the source image (step 110). The source image represents the image that would be approximated by a painting. As described above, the source image is provided to the processor 50 by the source generating arrangement 40 and/or by the storage device 80 which may already have the source image stored thereon. Other systems and/or devices may provide the source image to the processor 50. In step 120, the processor 50 receives a list of usable brush sizes and painting style instructions (e.g., data records) from the storage device 80 or from another source. The brush sizes and/or style can also be provided by a user via the user input device 20. In step 130, the processor fills a canvas image (e.g., image to be worked on) with a predetermined color. Then, in step 140, the processor 50 selects a largest brush size from the list of usable brush sizes to be used as a working brush (Ri).

Thereafter, the processor 50 digitally blurs the source image to generate a reference image (step 150). The source image may be preferably blurred using a convolution with a Gaussian kernel of standard deviation fσ * Ri, where fσ is a constant factor and Ri is the working brush size. Non-linear diffusion may also be used instead of the Gaussian blur to produce slightly better results near edges. Other standard blurring techniques can also be used. In step 160, the processor 50 executes instructions to paint the canvas image with the working brush using brush strokes. An embodiment of the method according to the present invention to paint the canvas image will be described below in further detail. The canvas image is painted over using the working brush (Ri) , based on the reference image (i.e., the blurred source image).

If all the brush sizes have not yet been utilized (step 170), the processor 50 assigns the next largest brush sized to be used for the working brush (step 180), blurs the source image to produce the reference image (step 150) and paints the canvas image again using the new working brush (i.e., returns to step 160). Each brush, preferably, captures only details which are at least as large as the size of the working brush currently used. If all the brush sizes have been utilized (step 170), the processor 50 stores the painted canvas image in the storage device 80 and/or displays the painted canvas image on the output device 30 via the output port 60 (step 190) and completes the execution of the method according to the present invention. The following is an exemplary pseudocode for the general method according to the present invention described above:

______________________________________
function paint(sourceImage, R1 . . . Rn)
canvas := a new constant color image
// paint the canvas
for each brush radius Ri,
from largest to smallest do
{
// apply Gaussian blur
referenceImage = sourceImage * G(fo Ri)
// paint a layer
paintLayer(canvas, referenceImage, Ri)
}
return canvas
}
______________________________________

FIGS. 4(b)-4(d) show a progression of the canvas image which uses the source image illustrated in FIG. 4(a). In particular, the canvas image is displayed in FIG. 4(b) after a first layer is digitally painted using a brush radius of 8 pixels (e.g., 8 mm). FIG. 4(c) shows the canvas image after being digitally painted over with the brush strokes, in which a brush having a radius of 4 pixels (e.g., 4 mm) is used.

FIG. 4(d) illustrates the final canvas image after being digitally painted over with brush strokes, in which a brush having a radius of 2 pixels (e.g., 2 mm) is used. It should be noted that the brush strokes of each size are still visible in FIG. 4(d).

FIG. 4(e) shows an exemplary illustration painted by Degas in 1876. It should be noted that a different character of painting strokes were used by the artist to depict a blouse, sand, children, boat and sky shown in this painting. In particular, each of these features were painted using brushes having different brush sizes, in addition to being painted using different stroke styles. This drawing illustrates that a variation in stroke quality helps to draw more attention to the woman and figures, while very little attention is drawn to the ground. Thus, the painter uses fine strokes to draw our attention to fine detail. Using this painting as a basis, the system and method of the present invention utilizes fine brush strokes which are used only where necessary to refine the painting, and leave the rest of the painting alone. Thus, an initial coarse approximation is painted on the canvas image, and then progressive refinements with smaller and smaller brushes are added thereto.

FIG. 5 shows an exemplary embodiment of a method according to the present invention for painting the canvas image with the working brush (i.e., detailing step 160 described above). In particular, the processor 50 cooperates the canvas image (e.g., overlays) with a grid (step 200). In step 210, if the working brush is the largest brush selected from a list of usable brush sizes (i.e., entering first pass over the canvas image), the processor performs steps 220-250. In step 220, a first grid location on the canvas image is determined (the next grid location is determined if the first grid location was previously determined). Then, in step 230, the processor 50 determines if the current grid location is equal to the last grid location. If so, the processor 50 returns the execution to step 170 as illustrated in FIG. 3. If not, the processor 50 executes commands to make a stroke which is normal to the gradient of the current grid location on the canvas image (step 250) (e.g., to draw a long, curved brush stroke) and the processor 50 returns the execution to step 220 where the next working grid location on the canvas image is determined and steps 230-250 are executed again.

If, in step 210, the next brush does not have the largest brush size (e.g., not entering the first pass), the processor 50 (in step 260) determines the difference (e.g., creating a difference image) between the canvas image and the reference image (i.e., the blurred image). The difference between the canvas image and the reference image (step 270 in FIG. 5) can be created in the following manner:

|(r1,g1,b1)-(r2,g2,b2)|=((r 1 -r2)2 +(g1 -g2)2 +(b1 -b2)2)1/2,

where r1, g1, b1 are color codes for the current grid point of the canvas image, and r2, g2, b2 are color codes for the corresponding grid point of the reference image. The next grid location on the canvas image is determined in step 270. In step 280, if the current grid location is the last grid location. If so, the processor 50 returns the execution to step 170 as illustrated in FIG. 3. If not, the processor 50 determines an average of the differences between the colors in the neighboring pixels around the current grid location and the corresponding pixels on the reference image. If the averaged difference is greater than a threshold value (step 300), the processor 50 determines the neighboring grid location on the canvas image having a greatest difference value (step 310), makes a stroke normal to the gradient of the current grid location on the canvas image (step 320), and returns to step 270 to move to a next grid location. Otherwise, the process returns to step 270, without making the stroke. As described above, the threshold value may be changed.

To summarize, each grid point's neighboring grid points (of the canvas image) are compared with the reference image's corresponding grid points to find the nearby point with the greatest error value (e.g., difference value), and the brush stroke is painted at that grid point. An exemplary pseudocode is shown below:

______________________________________
procedure paintLayer(canvas, referenceImage, R)
S := a new set of strokes, initially empty
// create a pointwise difference image
D := difference(canvas, referenceImage)
grid := fg R
for x=0 to imageWidth stepsize grid do
for y=0 to imageHeight stepsize grid do
// sum the error near (x,y)
M := the region (x-grid/2 . . . x+grid/2,
y-grid/2 . . . y+grid/2)
areaError := Di,j / grid2
if (areaError > T) then
{
// find the largest error point
(x1, y1) := arg max Di,j
s :=makeStroke (R, xi, yi, referenceImage)
add s to S
}
}
paint all strokes in S on the canvas,
in random order
}
______________________________________

The procedure --"makeStroke()"--places a stroke on the canvas image beginning at (x1,y1), which also accepts (as input) the reference image and the brush radius. fg is a constant grid size factor. FIG. 4(f) shows an image generated using the makeStroke() procedure which may place a circle of the brush radius at the grid location (x,y), using the color of the source image at location (x,y). FIG. 4(g) shows an image generated using short brush strokes, aligned to the normal direction of image gradients.

The method and system according to the present invention produces paintings that preferably focus viewer's attention to areas of the canvas image containing most of the details (e.g., high-frequency information) by placing many small brush strokes in these regions. Areas with small amount of detail are painted only with very large brush strokes. Thus, the strokes are appropriate to the level of detail in the source image. This choice of emphasis assumes that detail areas contain the most "important" visual information. Other choices of emphasis are also possible.

Placement of the Strokes

In one embodiment of the present invention, all strokes for each layer are planned (e.g., a data list stored in the storage device 80) before actually rendering (i.e., painting). Then, the strokes are rendered (e.g., displayed) in random order to prevent an undesirable appearance of regularity in the brush strokes.

In another embodiment of the present invention, a Z-buffer can be used to draw each stroke as soon as a stroke is created (i.e., without storing the strokes and then displaying them). Z-buffer is a computer graphics technique used for rendering 3D scenes. A Z-buffer is similar to a normal frame buffer which also stores an extra depth value (e.g., Z value) for each pixel (e.g., using the storage device 80). Thus, hidden surfaces for 3D models can be eliminated because every pixel includes data regarding its depth. If a pixel in the Z-buffer is attempted to be overwritten, the depths of the pixels are first compared. The new pixel is only written in the Z-buffer if it has a smaller depth value than the depth value of the current pixel. An exemplary C-language code for the procedure described above is as follows:

______________________________________
void writePixel(int x, int y, int color, byte depth)
if (zbuffer[x] [y].depth > depth)
{
zbuffer[x] [y].color = color;
zbuffer[x] [y].depth = depth;
}
}
______________________________________

In particular, for every grid location (e.g., a pixel) in the target image, a separate value (e.g., Z-value) is stored. Every Z value is initialized to 1 before each frame. A random value determined for the brush stroke (e.g., an R-value) is assigned a random number between 0 and 1. To paint a brush stroke, all of the pixels in the brush stroke are analyzed using the following procedure:

If the Z-value for a current pixel in the image is less than the R-value, nothing is done.

If the Z-value for the current pixel is greater than or equal to the R-value, then composite the strokes color over the current pixel, and set the Z-value for the current pixel to be equal to the R-value for the current pixel.

Creating Long Curved Brush Strokes

Individual brush strokes in a painting can convey shape, texture, overlap, and a variety of other image features. In the exemplary embodiment according to the present invention, step 320 (FIG. 5) can be implemented to draw a long, curved brush stroke to generate, for example, a gesture, a curve of an object or a play of light on a surface may be illustrated. The method and system according to the present invention enable a use of long curved brush strokes for painting long and continuous curves. In particular, these strokes of constant thickness are painted (i.e., generated) to approximate the colors of the reference image. The long curved brush strokes are provided as anti-aliased cubic B-splines, and each may include a predetermined color and opacity. Each stroke is rendered by dragging a circular brush mask along the sweep of the spline. In an exemplary embodiment of the present invention, the long curved brush strokes have a constant color and use image gradients to guide a placement of a stroke placement in a direction normal to the gradient of a particular image location. When the color of the stroke deviates from the color under the grid point of the reference image by more than a values of the current painting, the stroke ends at that control point. One can think of this as placing splines to roughly match the isocontours of the reference image.

A flowchart of an exemplary embodiment according to the present invention to make long curved strokes is illustrated in FIG. 6. The long curved stroke placement algorithm begins at a given point in the image (x0,y0), with a provided brush radius R. The control point (x0,y0) is added to the spline, and the color of the reference image at (x0,y0) is used as the color of the brush stroke. Additional control points are added by following the normals of the image gradient (as described below). The processor 50 then approximates the control points with a curved brush stroke. The brush stroke may be rendered with a cubic B-spline, with an anti-aliased circular mask drawn along the path of the curve, or using another conventional method.

In particular, in step 400, the processor 50 determines if the stroke length is greater than the maximum stroke length. If so, the process is returned to step 270 (shown in FIG. 5). If not, the processor 50 stops the stroke if the color of the stroke differs from the color under the last control point more than the reference image differs from the canvas image at that point. The processor 50, using steps 410-440, determines if the long curved stroke should be stopped. In particular, the processor 50 determines if the stroke length is greater than the minimum stroke length in step 410. (The minimum stroke length prevents the speckled appearance of very short strokes). If so, the processor 50 determines (in step 440) if the difference between the reference blurred image and the color of the stroke (step 420) is greater than the difference between the reference blurred image and the canvas image at the current grid location (step 430). If not, the process jumps to step 460, discussed below.

If either of steps 410 is answered in the negative or 440 is answered in the positive, the direction of the stroke (via control points) is determined in step 460, which is normal to the gradient of the corresponding grid location of the reference image. Then, in step 470, the control point is added to the stroke list (to determine the direction of the brush stroke), and the processor 50 prepares the brush to make the next brush stroke (step 480). Finally, the process returns to step 400.

The procedure according to the present invention generates points shown in FIGS. 7(a)-7(c). In particular, the processor 50 starts from the first point (x0,y0) (i.e., from the current grid location). The gradient (θ0) for this point (i.e., the grid location) can be computed, for example, from the Sobel-filtered luminance of the reference image; using other methods to compute the gradient (θ0) is also conceivable. The luminance of a pixel is computed as follows:

L(r,g,b)=0.30*r+0.59*g+0.11*b.

The next point (x1,y1) is placed in the direction (θ0 +π/2) at a distance R from (x0,y0), as illustrated in FIG. 7(a). The brush radius R is used as the distance between the grid locations because the brush radius R represents the level of preferred to be obtained using this brush size R. Accordingly, very large brushes create broad sketches of the canvas image, to be later refined with smaller radius brushes.

The remaining control points for the grid locations are computed by repeating the process according to the present invention (as shown in FIG. 6) by moving along the canvas image normal to the gradients and by placing control points. As provided in steps 400-450, the long curved stroke is terminated when (a) the predetermined maximum stroke length is reached, or (b) the color of the stroke differs from the color under the current grid location of the blurred reference image more than the color of the current grid point of the canvas image differs from the corresponding grid location of the blurred reference image, and that a minimum stroke length is reached. Thus, as shown in FIG. 7(b), the processor 50 computes a gradient direction θi at grid location (xi, yi). Since there may be two normal directions, i.e., θi +π/2, and θi -π/2., the next direction chosen minimizes the stroke curvature. Direction Di is selected so that the angle between Di and Di-1 is less than or equal to π/2. (See FIG. 7(b)). FIG. 7(c) illustrates further extensions of the long curved brush strokes.

The brush stroke curvatures can also be exaggerated or reduced by applying an infinite impulse response filter to the stroke directions. The filter can be controlled by a single predetermined filter constant --fc. If the previous stroke direction is determined as follows:

D'i-1 =(dx'i-1,dy'i-1),

and the current stroke direction is determined as:

Di =(dxi,dyi),

then the filtered stroke direction is:

______________________________________
D'i = fc Di + (1 - fc)D'i-1
= (fc dxi + (1 - fc) dx'i-1, fc
dyi + (1 - fc) dy'i-1).
______________________________________

An exemplary pseudocode of the procedure shown in FIG. 6 is as follows:

______________________________________
function makeSplineStroke(x0, y0, R, refImage)
strokeColor = refImage.color (x0, y0)
K = a new stroke with radius R and color strokeColor
add point (x0, y0) to K
(x, y) := (x0, y0)
(lastDx, lastDy) := (0, 0)
for I=1 to maxStrokeLength do
{
if (I > minStrokeLength and
|refImage.color(x, y) - canvas.color(x, y) |<
|refImage.color(x, y) - strokeColor|) then
return K
// detect vanishing gradient
if (refImage.gradientMag(x, y) == 0) then
return K
// get unit vector of gradient
(gx, gy) := refImage.gradientDirection(x, y)
// compute a normal direction
(dx, dy) := (-gy, gx)
// if necessary, reverse direction
if (lastDx * dx + lastDy * dy < 0) then
(dx,dy) := (-dx, -dy)
// filter the stroke direction
(dx, dy) := fc *(dx, dy) + (1 - fc)*(lastDx,lastDy)
(dx, dy) := (dx, dy)/(dx2 + dy2)1/2
(x, y) := (x+R*dx, y+R*dy)
(lastDx, lastDy) := (dx,dy)
add the point (x, y) to K
}
return K
}
______________________________________

Rendering Styles

The method and system according to the present invention allows a graphic designer or artist to vary the computer's "artistic approach," instead of being forced to employ a single style of painting for every picture. It is preferable to use style parameters to control the rendering process and the brush strokes. These parameters enable the graphic artist to vary visual qualities of the painting (e.g., the canvas image). Some exemplary style parameters include stroke curvature and how closely the painting should approximate the original image (e.g., the source image). To be useful to a designer, the style parameters may provide the following properties:

Intuitiveness: Each style parameter should correspond to a visual quality of the painting. These qualities should be intuitive to the graphic artist without requirement or necessity of any technical computer knowledge.

Consistency: Styles should produce a substantially similar "visual character" for different images. For example, the graphic arctic may select a style based on a single frame of a video sequence, and then render the rest of the sequence in the same style.

Robustness: Each parameter should produce reasonable results over a predetermined range, without distorting the image for some values. A default value may be provided, so that extra parameters provide the user with more options without adding any extra burden. Increasing a parameter preferably increases or decrease some quality of the painting, rather than cause the generated painting output to fluctuate.

Independence: Style parameters can preferably be independent of one another. Changing line thicknesses, for example, should not necessarily affect the saturation of the canvas image.

Styles may be designed to imitate the styles of famous artists, or may represent other approaches to painting. Styles may also be collected into libraries (e.g., as records) to be later used by the graphic designers. Using the parameters described below, the designer may simply adjust the parameters appropriate to a particular application.

Exemplary Style Parameters

The following style parameters may be used for the method and system according to the present invention:

Approximation Threshold (T): Indicates how closely should the painting (i.e., the canvas image) approximate the source image. For example, higher values of the threshold T generate "rougher" images. This threshold value may be utilized in the method according to the present invention in step 300.

Brush Sizes (R): According to the present invention, it may be preferable to use, e.g., three parameters to specify brush sizes--Smallest brush radius (R1), Number of Brushes (n), and Size Ratio (Ri+1 /Ri). A limited range of brush sizes may provide results that may match the graphic designer's requirements for the painting, as well as render the painting quickly.

Curvature Filter (fc): This parameter can be used to limit or exaggerate the stroke curvature.

Blur Factor (fσ): This parameter can control the size of the blurring kernel. A small blur factor allows more noise in the image, and thus produces a more "impressionistic" image.

Minimum/Maximum Stroke Lengths (minLength, maxLength): This parameter can be used to restrict the possible stroke lengths. Very short strokes may be used in a "pointillist" image, while long strokes may be used in a more "expressionistic" image.

Opacity (α): This parameter specifies the paint opacity, e.g., between 0 and 1. Lower opacity may produce a wash-like effect.

Grid size (fg): This parameter controls the spacing of brush strokes. The grid size times the brush radius (fg *Ri) can provide the step size in the "paintLayer()" procedure.

Color Jitter: This parameter randomly adds jitter to hue (jh), saturation (js), value (jv), red (jr), green (jg) or blue (jb) color components. A zero value may indicate no random jitter, while larger values increase the factor.

The threshold (T) can be defined in units of distance in color space. Brush sizes may be defined in units of distance. Sizes are specified in pixel units, although resolution-independent measures (such as inches or millimeters) can work equally well. Brush length can be measured using the number of control points. The remaining parameters are generally dimensionless.

Exemplary Utilization of Style Parameters

FIGS. 8(a)-8(b) show the application of the first three of these styles (i.e., "Impressionist", "Expressionist" and "Colorist Wash" in a top to bottom order) to two different images. The distinct character of each style demonstrates the consistency of the method and system according to the present invention. FIGS. 9(a)-9(c) show a continuous transition between the "Pointillist" style and the "Colorist Wash" style. In particular, FIG. 9(a) shows a painting in the "Colorist Wash" style and FIG. 9(c) shows the same painting in the "Pointillist" style. When the parameters of FIGS. 9(a) and 9(c) are averaged, a new style shown in FIG. 9(b) is generated. By interpolating style parameter values, the visual character of rendering styles can be interpolated.

The exemplary styles are as follows:

Impressionist--A normal painting style, with no curvature filter and no random color. Exemplary style parameters are as follows: T=100, R=(8,4,2), fc =1, fs =0.5, a=1, fg= 1, minLength=4, maxLength=16.

Expressionist--Elongated brush strokes. Jitter is added to color value. Exemplary style parameters are as follows: T=50, R=(8,4,2), fc =0.25, fs =0.5, a=0.7, fg =1, minLength=10, maxLength=16, jv =0.5.

Colorist Wash--Loose, semi-transparent brush strokes. Random jitter is added to R, G, and B color components. T=200, R=(8,4,2), fc =1, fs =0.5, a=0.5, fg =1, minLength=4, maxLength=16, jr =jg =jb =0.3.

Pointillist--Densely-placed circles with random hue and saturation. Exemplary style parameters are as follows: T=100, R=(4,2), fc =1, fs =0.5, a=1, fg =0.5, minLength=0, maxLength=0, jv =1, jh =0.3.

Another Exemplary Embodiment

The system and method according to the present invention can be used, e.g., in a Processing Video application. Some conventional methods for painting video sequences process each video frame separately, which produces a distracting `flickering` effect. To reduce this effect, and to improve temporal coherence, the system and method according to the present invention begins each frame by painting over the last frame of the animation, instead of starting with a blank canvas each time. This embodiment according to the present invention is very simple to implement, and is fast to compute, since relatively few brush strokes are rendered for each frame.

An exemplary steps of the embodiment described above is as follows:

a. A first frame of the video is processed using the system and method according to the present invention as shown in FIGS. 3, 5 and 6.

b. Each remaining frame of the video is processed with using the embodiment of the present invention described herein. In this embodiment, the initial canvas is the painting from the previous frame, rather than a blank canvas (e.g., step 130 of FIG. 3 is replaced with a step that copies the result of the previous frame). Then, the painting procedure is executed, however all layers are treated the same. Thus, steps 210-250 of FIG. 5 are eliminated, and step 200 is always followed by step 260.

c. The results of each painted frame are then combined into a new video sequence.

As such, this embodiment of the system and method according to the present invention can be equated to "painting" a movie by painting the first frame, then painting over the first frame to produce the second frame, etc.

Other Embodiments

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention. For example, it possible to utilize the system and method according to the present invention for animating a feature-length movie in a watercolor or oil painting style. Non-photo realistic rendering can also be used to create attractive and expressive images for graphic design and illustration. Furthermore, it is possible to modify the "makeLayer" procedure as shown in FIG. 5 to place the strokes in a different order. In addition, it is conceivable to modify the "makeSplineStroke()" procedure shown in FIG. 6 to place curved strokes differently. The brush stroke model may also include stroke thickness, tapering, stroke texture, tension, etc.

Perlin, Kenneth, Hertzmann, Aaron P.

Patent Priority Assignee Title
10147459, Sep 22 2016 Apple Inc. Artistic style transfer for videos
10198839, Sep 22 2016 Apple Inc. Style transfer-based image content correction
10636177, Nov 26 2014 Methods for creating a simulated watercolor-painted image from a source image
10664718, Sep 11 2017 Apple Inc. Real-time adjustment of hybrid DNN style transfer networks
10664963, Sep 11 2017 Apple Inc. Real-time selection of DNN style transfer networks from DNN sets
10789694, Sep 11 2017 Apple Inc. Real-time adjustment of temporal consistency constraints for video style
10909657, Sep 11 2017 Apple Inc. Flexible resolution support for image and video style transfer
11367163, May 31 2019 Apple Inc. Enhanced image processing techniques for deep neural networks
6310985, Jul 29 1998 MARTEK, INC Measuring angular rotation of an object
6633300, Dec 22 1999 Adobe Inc Method and apparatus for painting groups of objects
6711304, Jul 29 1998 MARTEK, INC Method and apparatus for measuring angular rotation of an object
6756974, Sep 24 1997 Canon Kabushiki Kaisha Display control apparatus and method
6791573, Apr 26 1999 Adobe Inc Smart erasure brush
6850274, Jul 15 1997 GOOGLE LLC Image texture mapping camera
6870550, Apr 26 1999 Adobe Inc Digital Painting
6891550, Mar 10 2000 Image manipulation software
6894694, Jul 15 1997 GOOGLE LLC Producing automatic “painting” effects in images
6970169, Sep 24 2002 Adobe Systems Incorporated Digitally synthesizing seamless texture having random variations
7092011, Jul 15 1997 GOOGLE LLC Camera for printing on media provided on print roll
7126609, Dec 22 1999 Adobe Inc Method and apparatus for painting groups of objects
7170523, Aug 14 2000 Fujitsu Limited Drawing-information processing apparatus and drawing-information processed method
7187404, Jul 15 1997 GOOGLE LLC Camera for printing manipulated images on media
7190373, Mar 10 2000 Alpha channel filter
7242799, May 25 2001 Method of generating painted or tile mosaic reproduction of a photograph or graphic image
7283162, Jul 15 1997 GOOGLE LLC Utilization of color transformation effects in photographs
7289156, Jul 15 1997 GOOGLE LLC Optical data card reader
7295211, Jul 15 1997 GOOGLE LLC Method of automatic image processing
7377706, Jul 15 1997 GOOGLE LLC Print media roll and ink supply cartridge
7391422, Dec 22 1999 Adobe Inc Method and apparatus for painting groups of objects
7400763, Apr 26 1999 Adobe Inc Smart erasure brush
7454085, Apr 29 2005 Hewlett-Packard Development Company, L.P. Method and apparatus for the creation of textures and borders for digital images
7460152, Jul 10 1998 GOOGLE LLC Camera for printing manipulated images
7466321, Jul 26 2005 HEWLETT-PACKARD DEVELOPMENT COMPANY, L P Method and apparatus for the creation of cartoon effect videos
7483050, Jul 10 1998 GOOGLE LLC Camera and controlling processing system
7545996, Apr 29 2005 Hewlett-Packard Development Company, L.P. Method and apparatus for the creation of image post-processing parameter curves
7593023, Jul 27 2005 Hewlett-Packard Development Company, L.P.; HEWLETT-PACKARD DEVELOPMENT COMPANY, L P Method and apparatus for the creation of randomized custom image effects
7602396, Dec 22 1999 Adobe Inc Method and apparatus for painting groups of objects
7602405, Mar 17 2006 Microsoft Technology Licensing, LLC Multiple brush components
7627168, Apr 26 1999 Adobe Inc Smart erasure brush
7760235, Jul 10 1998 GOOGLE LLC Image manipulation method for camera
7773113, Jul 15 1997 GOOGLE LLC Card based image manipulation method for camera
7774722, Jan 31 2006 Microsoft Technology Licensing, LLC Creation and manipulation of canvases based on ink strokes
7804521, Jul 15 1997 GOOGLE LLC Image manipulation camera
7817159, Apr 26 1999 Adobe Inc Digital painting
7821538, Jul 15 1997 GOOGLE LLC Camera printer operation method with media pull sensing
7920167, Apr 29 2005 Hewlett-Packard Development Company, L.P. Method and apparatus for the creation of image capture device parameter curves
7924313, Jul 15 1997 Memjet Technology Limited Camera device incorporating a print roll validation apparatus
7944473, Jul 15 1997 GOOGLE LLC Card based image manipulation method with card skew correction
7961249, Jul 15 1997 GOOGLE LLC Digital camera having interconnected image processing units
7969477, Jul 15 1997 Silverbrook Research Pty LTD Camera sensing device for capturing and manipulating images
7984965, Jul 15 1997 Memjet Technology Limited Print head unit with printhead and transport rollers
7995071, Dec 22 1999 Adobe Inc Method and apparatus for painting group of objects
8004584, Apr 29 2005 Hewlett-Packard Development Company, L.P. Method and apparatus for the creation of compound digital image effects
8013905, Jul 15 1997 GOOGLE LLC Method of processing images captured by digital camera to reduce distortion
8096642, Aug 11 1997 Memjet Technology Limited Inkjet nozzle with paddle layer arranged between first and second wafers
8102568, Jul 15 1997 GOOGLE LLC System for creating garments using camera and encoded card
8184925, Oct 22 2007 BERRIDGE, ROBERT O System for converting a photograph into a portrait-style image
8274665, Jul 15 1997 GOOGLE LLC Image sensing and printing device
8285137, Jul 15 1997 GOOGLE LLC Digital camera system for simultaneous printing and magnetic recording
8289326, Aug 16 2007 Southwest Research Institute Image analogy filters for terrain modeling
8421869, Jul 15 1997 GOOGLE LLC Camera system for with velocity sensor and de-blurring processor
8789939, Nov 09 1999 GOOGLE LLC Print media cartridge with ink supply manifold
8810723, Jul 15 1997 Google Inc. Quad-core image processor
8823823, Jul 15 1997 GOOGLE LLC Portable imaging device with multi-core processor and orientation sensor
8836809, Jul 15 1997 GOOGLE LLC Quad-core image processor for facial detection
8854492, Jul 15 1997 Google Inc. Portable device with image sensors and multi-core processor
8854493, Jul 15 1997 Google Inc. Hand held image capture device with multi-core processor for facial detection
8854494, Jul 15 1997 Google Inc. Portable hand-held device having stereoscopic image camera
8854538, Jul 15 1997 Google Inc. Quad-core image processor
8866923, May 25 1999 GOOGLE LLC Modular camera and printer
8866926, Jul 15 1997 GOOGLE LLC Multi-core processor for hand-held, image capture device
8872952, Jul 15 1997 Google Inc. Image capture and processing integrated circuit for a camera
8878953, Jul 15 1997 Google Inc. Digital camera with quad core processor
8885179, Jul 15 1997 Google Inc. Portable handheld device with multi-core image processor
8885180, Jul 15 1997 Google Inc. Portable handheld device with multi-core image processor
8890969, Jul 15 1997 Google Inc. Portable device with image sensors and multi-core processor
8890970, Jul 15 1997 Google Inc. Portable hand-held device having stereoscopic image camera
8891008, Jul 15 1997 Google Inc. Hand-held quad core processing apparatus
8896720, Jul 15 1997 GOOGLE LLC Hand held image capture device with multi-core processor for facial detection
8896724, Jul 15 1997 GOOGLE LLC Camera system to facilitate a cascade of imaging effects
8902324, Jul 15 1997 GOOGLE LLC Quad-core image processor for device with image display
8902333, Jul 15 1997 GOOGLE LLC Image processing method using sensed eye position
8902340, Jul 15 1997 GOOGLE LLC Multi-core image processor for portable device
8902357, Jul 15 1997 GOOGLE LLC Quad-core image processor
8908051, Jul 15 1997 GOOGLE LLC Handheld imaging device with system-on-chip microcontroller incorporating on shared wafer image processor and image sensor
8908069, Jul 15 1997 GOOGLE LLC Handheld imaging device with quad-core image processor integrating image sensor interface
8908075, Jul 15 1997 GOOGLE LLC Image capture and processing integrated circuit for a camera
8913137, Jul 15 1997 GOOGLE LLC Handheld imaging device with multi-core image processor integrating image sensor interface
8913151, Jul 15 1997 GOOGLE LLC Digital camera with quad core processor
8913182, Jul 15 1997 GOOGLE LLC Portable hand-held device having networked quad core processor
8922548, Jan 20 2012 SSO VENTURE PARTNERS LLC System and method of pointillist painting design
8922670, Jul 15 1997 GOOGLE LLC Portable hand-held device having stereoscopic image camera
8922791, Jul 15 1997 GOOGLE LLC Camera system with color display and processor for Reed-Solomon decoding
8928897, Jul 15 1997 GOOGLE LLC Portable handheld device with multi-core image processor
8934027, Jul 15 1997 GOOGLE LLC Portable device with image sensors and multi-core processor
8934053, Jul 15 1997 GOOGLE LLC Hand-held quad core processing apparatus
8936196, Jul 15 1997 GOOGLE LLC Camera unit incorporating program script scanner
8937727, Jul 15 1997 GOOGLE LLC Portable handheld device with multi-core image processor
8947592, Jul 15 1997 GOOGLE LLC Handheld imaging device with image processor provided with multiple parallel processing units
8947679, Jul 15 1997 GOOGLE LLC Portable handheld device with multi-core microcoded image processor
8952939, Oct 26 2010 Nomadbrush LLC Conductive brush for use with a computing device
8953060, Jul 15 1997 GOOGLE LLC Hand held image capture device with multi-core processor and wireless interface to input device
8953061, Jul 15 1997 GOOGLE LLC Image capture device with linked multi-core processor and orientation sensor
8953178, Jul 15 1997 GOOGLE LLC Camera system with color display and processor for reed-solomon decoding
8988418, Jan 05 2007 Florelle, Inc. System and method for parametric display of modular aesthetic designs
8988461, Jan 18 2011 DISNEY ENTERPRISES, INC 3D drawing and painting system with a 3D scalar field
9013717, Jul 15 1997 Google Inc. Handheld imaging device with multi-core image processor integrating common bus interface and dedicated image sensor interface
9036162, Jul 15 1997 Google Inc. Image sensing and printing device
9036938, May 23 2012 Sony Corporation Image processing apparatus, image processing method, and program
9044965, Dec 12 1997 Google Inc. Disposable digital camera with printing assembly
9049318, Jul 15 1997 Google Inc. Portable hand-held device for displaying oriented images
9055221, Jul 15 1997 GOOGLE LLC Portable hand-held device for deblurring sensed images
9060081, Jul 15 1997 Google Inc. Handheld imaging device with multi-core image processor integrating common bus interface and dedicated image sensor interface
9060128, Jul 15 1997 GOOGLE LLC Portable hand-held device for manipulating images
9083829, Jul 15 1997 Google Inc. Portable hand-held device for displaying oriented images
9083830, Jul 15 1997 Google Inc. Portable device with image sensor and quad-core processor for multi-point focus image capture
9088675, Jul 15 1997 Google Inc. Image sensing and printing device
9100516, Jul 15 1997 Google Inc. Portable imaging device with multi-core processor
9106775, Jul 15 1997 Google Inc. Multi-core processor for portable device with dual image sensors
9108430, Dec 12 1997 Google Inc. Disposable digital camera with printing assembly
9113007, Jul 15 1997 Google Inc. Camera with linked parallel processor cores
9113008, Jul 15 1997 Google Inc. Handheld imaging device with multi-core image processor integrating common bus interface and dedicated image sensor interface
9113009, Jul 15 1997 Google Inc. Portable device with dual image sensors and quad-core processor
9113010, Jul 15 1997 Google Inc. Portable hand-held device having quad core image processor
9124735, Jul 15 1997 Google Inc. Camera system comprising color display and processor for decoding data blocks in printed coding pattern
9124736, Jul 15 1997 GOOGLE LLC Portable hand-held device for displaying oriented images
9124737, Jul 15 1997 GOOGLE LLC Portable device with image sensor and quad-core processor for multi-point focus image capture
9131083, Jul 15 1997 GOOGLE LLC Portable imaging device with multi-core processor
9137397, Jul 15 1997 GOOGLE LLC Image sensing and printing device
9137398, Jul 15 1997 GOOGLE LLC Multi-core processor for portable device with dual image sensors
9142056, May 18 2011 DISNEY ENTERPRISES, INC Mixed-order compositing for images having three-dimensional painting effects
9143635, Jul 15 1997 GOOGLE LLC Camera with linked parallel processor cores
9143636, Jul 15 1997 GOOGLE LLC Portable device with dual image sensors and quad-core processor
9148530, Jul 15 1997 GOOGLE LLC Handheld imaging device with multi-core image processor integrating common bus interface and dedicated image sensor interface
9154647, Jul 15 1997 Google Inc. Central processor with multiple programmable processor units
9154648, Jul 15 1997 Google Inc. Portable hand-held device having quad core image processor
9167109, Jul 15 1997 Google Inc. Digital camera having image processor and printer
9168761, Dec 12 1997 GOOGLE LLC Disposable digital camera with printing assembly
9179020, Jul 15 1997 GOOGLE LLC Handheld imaging device with integrated chip incorporating on shared wafer image processor and central processor
9185246, Jul 15 1997 GOOGLE LLC Camera system comprising color display and processor for decoding data blocks in printed coding pattern
9185247, Jul 15 1997 GOOGLE LLC Central processor with multiple programmable processor units
9191529, Jul 15 1997 GOOGLE LLC Quad-core camera processor
9191530, Jul 15 1997 GOOGLE LLC Portable hand-held device having quad core image processor
9197767, Jul 15 1997 GOOGLE LLC Digital camera having image processor and printer
9219832, Jul 15 1997 GOOGLE LLC Portable handheld device with multi-core image processor
9237244, Jul 15 1997 GOOGLE LLC Handheld digital camera device with orientation sensing and decoding capabilities
9304682, Jan 31 2006 Microsoft Technology Licensing, LLC Creation and manipulation of canvases based on ink strokes
9305398, Oct 08 2010 City University of Hong Kong Methods for creating and displaying two and three dimensional images on a digital canvas
9338312, Jul 10 1998 GOOGLE LLC Portable handheld device with multi-core image processor
9396558, Sep 02 2011 Sony Corporation Image processing apparatus and method, and program
9432529, Jul 15 1997 GOOGLE LLC Portable handheld device with multi-core microcoded image processor
9544451, Jul 15 1997 GOOGLE LLC Multi-core image processor for portable device
9550209, Jan 20 2012 SSO Venture Partners, LLC System and method of pointillist painting
9560221, Jul 15 1997 GOOGLE LLC Handheld imaging device with VLIW image processor
9584681, Jul 15 1997 GOOGLE LLC Handheld imaging device incorporating multi-core image processor
Patent Priority Assignee Title
4633416, Dec 04 1980 Quantel Limited Video image creation system which simulates drafting tool
4956872, Oct 31 1986 Canon Kabushiki Kaisha Image processing apparatus capable of random mosaic and/or oil-painting-like processing
5038223, Feb 29 1988 Canon Kabushiki Kaisha Image processing method and apparatus for imparting a pictorial or painter-like effect
5063448, Jul 31 1989 AVID TECHNOLOGY, INC Apparatus and method for transforming a digitized signal of an image
5276786, Sep 05 1988 Quantel Limited Video graphics systems separately processing an area of the picture before blending the processed area into the original picture
5301136, Mar 17 1992 Sun Microsystems, Inc. Method and apparatus for fast implementation of inverse discrete cosine transform in a digital image processing system using low cost accumulators
5384912, Oct 30 1987 NEW MICROTIME INC Real time video image processing system
5412767, May 17 1989 Quantel, Ltd. Image processing system utilizing brush profile
5500925, Dec 01 1992 Xaos Tools Dynamic image processing using particle systems
5621868, Apr 15 1994 Sony Corporation; Sony Electronics, INC Generating imitation custom artwork by simulating brush strokes and enhancing edges
5687304, Feb 14 1994 Parametric Technology Corporation Real-time image generation system for simulating physical paint, drawing media, and feature modeling with 3-D graphics
///
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May 21 1998HERTZMANN, AARON P New York UniversityASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS 0092280453 pdf
May 22 1998New York University(assignment on the face of the patent)
May 22 1998PERLIN, KENNETH New York UniversityASSIGNMENT OF ASSIGNORS INTEREST SEE DOCUMENT FOR DETAILS 0092280453 pdf
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